Physicochemical parameters, retention analyte

Much effort has been devoted to the development of reliable calculation methods for the prediction of the retention behaviour of analyses with well-known chemical structure and physicochemical parameters. Calculations can facilitate the rapid optimization of the separation process, reducing the number of preliminary experiments required for optimization. It has been earlier recognized that only one physicochemical parameter is not sufficient for the prediction of the retention of analyte in any RP-HPLC system. One of the most popular multivariate models for the calculation of the retention parameters of analyte is the linear solvation energy relationship (LSER) ... 

It should be stressed that Equation 12.13 is approximated and it should be used cautiously to calculate physicochemical parameters from the retention data because of the associated error. However, it can be useful to obtain simplified, approximated relationships between retention and field-particle interaction as will be detailed below for the specific FEE techniques. The physicochemical parameters of the analytes can be calculated when Equation 12.11 is used in association with the pertinent X expression. Table 12.1 reports the explicit expressions of X for different subtechniques. Examples of... 

The classical FEE retention equation (see Equation 12.11) does not apply to ThEEE since relevant physicochemical parameters—affecting both flow profile and analyte concentration distribution in the channel cross section—are temperature dependent and thus not constant in the channel cross-sectional area. Inside the channel, the flow of solvent carrier follows a distorted, parabolic flow profile because of the changing values of the carrier properties along the channel thickness (density, viscosity, and thermal conductivity). Under these conditions, the concentration profile differs from the exponential profile since the velocity profile is strongly distorted with respect to the parabolic profile. By taking into account these effects, the ThEEE retention equation (see Equation 12.11) becomes ... 

The choice of the FFF technique dictates which physicochemical parameters of the analyte govern its retention in the channel FIFFF separates solely by size, SdFFF by both size and density, ThFFF by size and chanical composition, and EIFFF by mass and charge. The dependence of retention on factors other than size can be advantageous in some applications, and different information can be obtained by employing different techniques in combination or in sequence. On the other hand, the properties that can be characterized by FFF include analyte mass, density, volume, diffusion coefficient, charge, electrophoretic mobility, p/ (isoelectric point), molecular weight, and particle diameter. 

The empirical physicochemical parameters have a good informative value for determining the mechanism of retention operating in a given chromatographic sy.stem. There are exhaustive compilations of such parameters like >/-octanol-water partition coefficients [45,46] or the LSER-based analyte parameters [47,48]. The problem is. however, that there is a lack of such descriptors for many analytes of interest in actual QSRR studies. 

In field-flow fractionation (FFF), retention can be related through a well-defined equation to the applied held and governing physicochemical parameters of the analyte. Therefore, in principle, FFF is a primary measurement technique that does not require calibration, but only if the governing physiochemical parameters are either the analyte parameters of interest or their relationship to the parameter of interest (such a molecular weight) is well deflned. 

Besides MS detection, identification of unknown peaks in GC routine analysis of environmental samples can be aided by the use of correlations between physicochemical parameters and structure of the analytes to predict the retention times. The correlation between the boiling points and the retention times of chloro- and bromo-benzenes and of some chloro- and nitro-substituted phenols was investigated for nonpolar capillary columns and allowed tentative identification of many compounds belonging to these analogous series. ... 

The second level of computer utilization in HPLC is extraction of valuable analytical and physicochemical information from the chromatogram. This includes standard analytical procedures of peak integration, calibration and quantitation, and more complex correlation of the retention dependencies with variation of selected parameters. 

From their QSERR they find solute lipophilicity and steric properties as being responsible for analyte retention (k ) while enantioseparation (a) varied mainly with electronic and steric properties. The main difference between the analytes is that the enantioseparation of the esters is correlated with steric parameters that scale linearly with log a while the sulfoxides scale nonlinearly (parabolic), but this may be due to a computational artifact. The 3D-QSERR derived from field analysis revealed that while superpositioning of field maps for both analytes are not exactly the same, a similar balance of physicochemical forces involved in the chiral recognition process are at play for both sets of analyes. This type of atomistic molecular modeling, then, is a powerful adjunct to the type of modeling described earlier in this chapter and will, no doubt, be used more frequently in future studies. 

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